Overview

Dataset statistics

 Profiling ReportTransformed Data
Number of variables2323
Number of observations10127158
Missing cells00
Missing cells (%)0.0%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory1.8 MiB29.6 KiB
Average record size in memory184.0 B192.0 B

Variable types

 Profiling ReportTransformed Data
Numeric1717
Categorical66

Alerts

Profiling ReportTransformed Data
Customer_Age is highly overall correlated with Months_on_bookCustomer_Age is highly overall correlated with Months_on_bookHigh Correlation
Months_on_book is highly overall correlated with Customer_AgeMonths_on_book is highly overall correlated with Customer_AgeHigh Correlation
Months_Inactive_12_mon is highly overall correlated with Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 and 1 other fieldsMonths_Inactive_12_mon is highly overall correlated with Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 and 1 other fieldsHigh Correlation
Contacts_Count_12_mon is highly overall correlated with Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 and 1 other fieldsContacts_Count_12_mon is highly overall correlated with Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 and 1 other fieldsHigh Correlation
Credit_Limit is highly overall correlated with Avg_Open_To_BuyCredit_Limit is highly overall correlated with Avg_Open_To_Buy and 1 other fieldsHigh Correlation
Total_Revolving_Bal is highly overall correlated with Avg_Utilization_RatioTotal_Revolving_Bal is highly overall correlated with Attrition_FlagHigh Correlation
Avg_Open_To_Buy is highly overall correlated with Credit_Limit and 1 other fieldsAvg_Open_To_Buy is highly overall correlated with Credit_Limit and 1 other fieldsHigh Correlation
Total_Trans_Amt is highly overall correlated with Total_Trans_CtTotal_Trans_Amt is highly overall correlated with Total_Trans_CtHigh Correlation
Total_Trans_Ct is highly overall correlated with Total_Trans_AmtTotal_Trans_Ct is highly overall correlated with Total_Trans_Amt and 1 other fieldsHigh Correlation
Avg_Utilization_Ratio is highly overall correlated with Total_Revolving_Bal and 1 other fieldsAvg_Utilization_Ratio is highly overall correlated with Credit_Limit and 1 other fieldsHigh Correlation
Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 is highly overall correlated with Months_Inactive_12_mon and 3 other fieldsNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 is highly overall correlated with Months_Inactive_12_mon and 3 other fieldsHigh Correlation
Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2 is highly overall correlated with Months_Inactive_12_mon and 3 other fieldsNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2 is highly overall correlated with Months_Inactive_12_mon and 3 other fieldsHigh Correlation
Attrition_Flag is highly overall correlated with Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1 and 1 other fieldsAttrition_Flag is highly overall correlated with Total_Revolving_Bal and 3 other fieldsHigh Correlation
Gender is highly overall correlated with Income_CategoryGender is highly overall correlated with Income_CategoryHigh Correlation
Income_Category is highly overall correlated with GenderIncome_Category is highly overall correlated with GenderHigh Correlation
Card_Category is highly imbalanced (79.2%) Alert not present in this datasetImbalance
CLIENTNUM has unique values CLIENTNUM has unique values Unique
Dependent_count has 904 (8.9%) zeros Dependent_count has 15 (9.5%) zeros Zeros
Contacts_Count_12_mon has 399 (3.9%) zeros Contacts_Count_12_mon has 10 (6.3%) zeros Zeros
Total_Revolving_Bal has 2470 (24.4%) zeros Alert not present in this datasetZeros
Avg_Utilization_Ratio has 2470 (24.4%) zeros Alert not present in this datasetZeros
Alert not present in this datasetCard_Category has constant value "" Constant

Reproduction

 Profiling ReportTransformed Data
Analysis started2023-11-09 08:54:11.3541492023-11-09 08:54:53.148502
Analysis finished2023-11-09 08:54:33.3833442023-11-09 08:55:12.505618
Duration22.03 seconds19.36 seconds
Software versionydata-profiling vv4.6.1ydata-profiling vv4.6.1
Download configurationconfig.jsonconfig.json

Variables

CLIENTNUM
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct10127158
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean7.3917761 × 1087.4247182 × 108
 Profiling ReportTransformed Data
Minimum7.0808208 × 1087.0839701 × 108
Maximum8.2834308 × 1088.2828833 × 108
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:12.591972image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum7.0808208 × 1087.0839701 × 108
5-th percentile7.0912039 × 1087.098795 × 108
Q17.1303677 × 1087.1410218 × 108
median7.1792636 × 1087.177149 × 108
Q37.7314353 × 1087.7950177 × 108
95-th percentile8.1421203 × 1088.190501 × 108
Maximum8.2834308 × 1088.2828833 × 108
Range1.20261 × 1081.1989132 × 108
Interquartile range (IQR)6010676265399588

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation3690378339299580
Coefficient of variation (CV)0.0499254620.052930737
Kurtosis-0.6156397-0.84528214
Mean7.3917761 × 1087.4247182 × 108
Median Absolute Deviation (MAD)63477005567212.5
Skewness0.995601010.89019404
Sum7.4856516 × 10121.1731055 × 1011
Variance1.3618892 × 10151.544457 × 1015
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:12.736681image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
768805383 1
 
< 0.1%
711784908 1
 
< 0.1%
720133908 1
 
< 0.1%
803197833 1
 
< 0.1%
812222208 1
 
< 0.1%
757634583 1
 
< 0.1%
719362458 1
 
< 0.1%
789331908 1
 
< 0.1%
715616358 1
 
< 0.1%
806900508 1
 
< 0.1%
Other values (10117) 10117
99.9%
ValueCountFrequency (%)
715190283 1
 
0.6%
712613808 1
 
0.6%
820868508 1
 
0.6%
789095958 1
 
0.6%
708397008 1
 
0.6%
779405133 1
 
0.6%
789907533 1
 
0.6%
823908858 1
 
0.6%
716689383 1
 
0.6%
715418508 1
 
0.6%
Other values (148) 148
93.7%
ValueCountFrequency (%)
708082083 1
< 0.1%
708083283 1
< 0.1%
708084558 1
< 0.1%
708085458 1
< 0.1%
708086958 1
< 0.1%
708095133 1
< 0.1%
708098133 1
< 0.1%
708099183 1
< 0.1%
708100533 1
< 0.1%
708103608 1
< 0.1%
ValueCountFrequency (%)
708397008 1
0.6%
708426483 1
0.6%
708702258 1
0.6%
708880683 1
0.6%
709094358 1
0.6%
709273383 1
0.6%
709310433 1
0.6%
709788783 1
0.6%
709895508 1
0.6%
710357208 1
0.6%
ValueCountFrequency (%)
708397008 1
< 0.1%
708426483 1
< 0.1%
708702258 1
< 0.1%
708880683 1
< 0.1%
709094358 1
< 0.1%
709273383 1
< 0.1%
709310433 1
< 0.1%
709788783 1
< 0.1%
709895508 1
< 0.1%
710357208 1
< 0.1%
ValueCountFrequency (%)
708082083 1
0.6%
708083283 1
0.6%
708084558 1
0.6%
708085458 1
0.6%
708086958 1
0.6%
708095133 1
0.6%
708098133 1
0.6%
708099183 1
0.6%
708100533 1
0.6%
708103608 1
0.6%

Attrition_Flag
Categorical

 Profiling ReportTransformed Data
Distinct22
Distinct (%)< 0.1%1.3%
Missing00
Missing (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
Existing Customer
8500 
Attrited Customer
1627 
Existing Customer
127 
Attrited Customer
31 

Length

 Profiling ReportTransformed Data
Max length1717
Median length1717
Mean length1717
Min length1717

Characters and Unicode

 Profiling ReportTransformed Data
Total characters1721592686
Distinct characters1616
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling ReportTransformed Data
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling ReportTransformed Data
1st rowExisting CustomerExisting Customer
2nd rowExisting CustomerExisting Customer
3rd rowExisting CustomerExisting Customer
4th rowExisting CustomerAttrited Customer
5th rowExisting CustomerExisting Customer

Common Values

ValueCountFrequency (%)
Existing Customer 8500
83.9%
Attrited Customer 1627
 
16.1%
ValueCountFrequency (%)
Existing Customer 127
80.4%
Attrited Customer 31
 
19.6%

Length

2023-11-09T11:55:12.821133image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report

2023-11-09T11:55:12.884149image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:12.946655image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
customer 10127
50.0%
existing 8500
42.0%
attrited 1627
 
8.0%
ValueCountFrequency (%)
customer 158
50.0%
existing 127
40.2%
attrited 31
 
9.8%

Most occurring characters

ValueCountFrequency (%)
t 23508
13.7%
i 18627
10.8%
s 18627
10.8%
e 11754
 
6.8%
r 11754
 
6.8%
10127
 
5.9%
C 10127
 
5.9%
u 10127
 
5.9%
o 10127
 
5.9%
m 10127
 
5.9%
Other values (6) 37254
21.6%
ValueCountFrequency (%)
t 378
14.1%
i 285
10.6%
s 285
10.6%
e 189
 
7.0%
r 189
 
7.0%
158
 
5.9%
C 158
 
5.9%
u 158
 
5.9%
o 158
 
5.9%
m 158
 
5.9%
Other values (6) 570
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 141778
82.4%
Uppercase Letter 20254
 
11.8%
Space Separator 10127
 
5.9%
ValueCountFrequency (%)
Lowercase Letter 2212
82.4%
Uppercase Letter 316
 
11.8%
Space Separator 158
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 23508
16.6%
i 18627
13.1%
s 18627
13.1%
e 11754
8.3%
r 11754
8.3%
u 10127
7.1%
o 10127
7.1%
m 10127
7.1%
x 8500
 
6.0%
n 8500
 
6.0%
Other values (2) 10127
7.1%
ValueCountFrequency (%)
t 378
17.1%
i 285
12.9%
s 285
12.9%
e 189
8.5%
r 189
8.5%
u 158
7.1%
o 158
7.1%
m 158
7.1%
x 127
 
5.7%
n 127
 
5.7%
Other values (2) 158
7.1%
Space Separator
ValueCountFrequency (%)
10127
100.0%
ValueCountFrequency (%)
158
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 10127
50.0%
E 8500
42.0%
A 1627
 
8.0%
ValueCountFrequency (%)
C 158
50.0%
E 127
40.2%
A 31
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 162032
94.1%
Common 10127
 
5.9%
ValueCountFrequency (%)
Latin 2528
94.1%
Common 158
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 23508
14.5%
i 18627
11.5%
s 18627
11.5%
e 11754
7.3%
r 11754
7.3%
C 10127
 
6.2%
u 10127
 
6.2%
o 10127
 
6.2%
m 10127
 
6.2%
E 8500
 
5.2%
Other values (5) 28754
17.7%
ValueCountFrequency (%)
t 378
15.0%
i 285
11.3%
s 285
11.3%
e 189
7.5%
r 189
7.5%
C 158
 
6.2%
u 158
 
6.2%
o 158
 
6.2%
m 158
 
6.2%
E 127
 
5.0%
Other values (5) 443
17.5%
Common
ValueCountFrequency (%)
10127
100.0%
ValueCountFrequency (%)
158
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172159
100.0%
ValueCountFrequency (%)
ASCII 2686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 23508
13.7%
i 18627
10.8%
s 18627
10.8%
e 11754
 
6.8%
r 11754
 
6.8%
10127
 
5.9%
C 10127
 
5.9%
u 10127
 
5.9%
o 10127
 
5.9%
m 10127
 
5.9%
Other values (6) 37254
21.6%
ValueCountFrequency (%)
t 378
14.1%
i 285
10.6%
s 285
10.6%
e 189
 
7.0%
r 189
 
7.0%
158
 
5.9%
C 158
 
5.9%
u 158
 
5.9%
o 158
 
5.9%
m 158
 
5.9%
Other values (6) 570
21.2%

Customer_Age
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct4533
Distinct (%)0.4%20.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean46.3259647.829114
 Profiling ReportTransformed Data
Minimum2630
Maximum7365
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:13.040867image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum2630
5-th percentile3335.85
Q14143
median4648
Q35252
95-th percentile6061
Maximum7365
Range4735
Interquartile range (IQR)119

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation8.0168147.4021799
Coefficient of variation (CV)0.17305230.15476306
Kurtosis-0.28861992-0.19481356
Mean46.3259647.829114
Median Absolute Deviation (MAD)65
Skewness-0.0336050160.073355251
Sum4691437557
Variance64.26930754.792268
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:13.150633image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
44 500
 
4.9%
49 495
 
4.9%
46 490
 
4.8%
45 486
 
4.8%
47 479
 
4.7%
43 473
 
4.7%
48 472
 
4.7%
50 452
 
4.5%
42 426
 
4.2%
51 398
 
3.9%
Other values (35) 5456
53.9%
ValueCountFrequency (%)
51 14
 
8.9%
45 13
 
8.2%
50 10
 
6.3%
47 9
 
5.7%
49 9
 
5.7%
48 8
 
5.1%
54 7
 
4.4%
37 7
 
4.4%
56 7
 
4.4%
44 6
 
3.8%
Other values (23) 68
43.0%
ValueCountFrequency (%)
26 78
0.8%
27 32
 
0.3%
28 29
 
0.3%
29 56
 
0.6%
30 70
 
0.7%
31 91
0.9%
32 106
1.0%
33 127
1.3%
34 146
1.4%
35 184
1.8%
ValueCountFrequency (%)
30 1
 
0.6%
31 1
 
0.6%
34 4
2.5%
35 2
 
1.3%
36 2
 
1.3%
37 7
4.4%
38 2
 
1.3%
39 4
2.5%
40 4
2.5%
41 3
1.9%
ValueCountFrequency (%)
30 1
 
< 0.1%
31 1
 
< 0.1%
34 4
< 0.1%
35 2
 
< 0.1%
36 2
 
< 0.1%
37 7
0.1%
38 2
 
< 0.1%
39 4
< 0.1%
40 4
< 0.1%
41 3
< 0.1%
ValueCountFrequency (%)
26 78
49.4%
27 32
 
20.3%
28 29
 
18.4%
29 56
 
35.4%
30 70
 
44.3%
31 91
57.6%
32 106
67.1%
33 127
80.4%
34 146
92.4%
35 184
116.5%

Gender
Categorical

 Profiling ReportTransformed Data
Distinct22
Distinct (%)< 0.1%1.3%
Missing00
Missing (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
F
5358 
M
4769 
F
86 
M
72 

Length

 Profiling ReportTransformed Data
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Profiling ReportTransformed Data
Total characters10127158
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling ReportTransformed Data
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling ReportTransformed Data
1st rowMF
2nd rowFF
3rd rowMF
4th rowFF
5th rowMM

Common Values

ValueCountFrequency (%)
F 5358
52.9%
M 4769
47.1%
ValueCountFrequency (%)
F 86
54.4%
M 72
45.6%

Length

2023-11-09T11:55:13.229177image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report

2023-11-09T11:55:13.299257image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:13.361277image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
f 5358
52.9%
m 4769
47.1%
ValueCountFrequency (%)
f 86
54.4%
m 72
45.6%

Most occurring characters

ValueCountFrequency (%)
F 5358
52.9%
M 4769
47.1%
ValueCountFrequency (%)
F 86
54.4%
M 72
45.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10127
100.0%
ValueCountFrequency (%)
Uppercase Letter 158
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 5358
52.9%
M 4769
47.1%
ValueCountFrequency (%)
F 86
54.4%
M 72
45.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 10127
100.0%
ValueCountFrequency (%)
Latin 158
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 5358
52.9%
M 4769
47.1%
ValueCountFrequency (%)
F 86
54.4%
M 72
45.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10127
100.0%
ValueCountFrequency (%)
ASCII 158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 5358
52.9%
M 4769
47.1%
ValueCountFrequency (%)
F 86
54.4%
M 72
45.6%

Dependent_count
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct66
Distinct (%)0.1%3.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.34620322.4113924
 Profiling ReportTransformed Data
Minimum00
Maximum55
Zeros90415
Zeros (%)8.9%9.5%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:13.424350image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum00
5-th percentile00
Q112
median22
Q333
95-th percentile44
Maximum55
Range55
Interquartile range (IQR)21

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation1.29890831.2675758
Coefficient of variation (CV)0.553621420.52566135
Kurtosis-0.68301665-0.38155799
Mean2.34620322.4113924
Median Absolute Deviation (MAD)11
Skewness-0.020825536-0.14992776
Sum23760381
Variance1.68716291.6067484
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:13.487424image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2732
27.0%
2 2655
26.2%
1 1838
18.1%
4 1574
15.5%
0 904
 
8.9%
5 424
 
4.2%
ValueCountFrequency (%)
3 49
31.0%
2 46
29.1%
4 22
13.9%
1 19
 
12.0%
0 15
 
9.5%
5 7
 
4.4%
ValueCountFrequency (%)
0 904
 
8.9%
1 1838
18.1%
2 2655
26.2%
3 2732
27.0%
4 1574
15.5%
5 424
 
4.2%
ValueCountFrequency (%)
0 15
 
9.5%
1 19
 
12.0%
2 46
29.1%
3 49
31.0%
4 22
13.9%
5 7
 
4.4%
ValueCountFrequency (%)
0 15
 
0.1%
1 19
 
0.2%
2 46
0.5%
3 49
0.5%
4 22
0.2%
5 7
 
0.1%
ValueCountFrequency (%)
0 904
 
572.2%
1 1838
1163.3%
2 2655
1680.4%
3 2732
1729.1%
4 1574
996.2%
5 424
 
268.4%

Education_Level
Categorical

 Profiling ReportTransformed Data
Distinct75
Distinct (%)0.1%3.2%
Missing00
Missing (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
Graduate
3128 
High School
2013 
Unknown
1519 
Uneducated
1487 
College
1013 
Other values (2)
967 
Graduate
78 
Uneducated
29 
Unknown
25 
College
15 
Doctorate
11 

Length

 Profiling ReportTransformed Data
Max length1310
Median length119
Mean length8.93927138.1835443
Min length77

Characters and Unicode

 Profiling ReportTransformed Data
Total characters905281293
Distinct characters2517
Distinct categories42 ?
Distinct scripts21 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling ReportTransformed Data
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling ReportTransformed Data
1st rowHigh SchoolGraduate
2nd rowGraduateGraduate
3rd rowGraduateUneducated
4th rowHigh SchoolUneducated
5th rowUneducatedUnknown

Common Values

ValueCountFrequency (%)
Graduate 3128
30.9%
High School 2013
19.9%
Unknown 1519
15.0%
Uneducated 1487
14.7%
College 1013
 
10.0%
Post-Graduate 516
 
5.1%
Doctorate 451
 
4.5%
ValueCountFrequency (%)
Graduate 78
49.4%
Uneducated 29
 
18.4%
Unknown 25
 
15.8%
College 15
 
9.5%
Doctorate 11
 
7.0%

Length

2023-11-09T11:55:13.581695image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report

2023-11-09T11:55:13.659886image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:13.738605image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
graduate 3128
25.8%
high 2013
16.6%
school 2013
16.6%
unknown 1519
12.5%
uneducated 1487
12.2%
college 1013
 
8.3%
post-graduate 516
 
4.3%
doctorate 451
 
3.7%
ValueCountFrequency (%)
graduate 78
49.4%
uneducated 29
 
18.4%
unknown 25
 
15.8%
college 15
 
9.5%
doctorate 11
 
7.0%

Most occurring characters

ValueCountFrequency (%)
a 9226
 
10.2%
e 9095
 
10.0%
o 7976
 
8.8%
d 6618
 
7.3%
t 6549
 
7.2%
n 6044
 
6.7%
u 5131
 
5.7%
r 4095
 
4.5%
l 4039
 
4.5%
h 4026
 
4.4%
Other values (15) 27729
30.6%
ValueCountFrequency (%)
a 196
15.2%
e 177
13.7%
d 136
10.5%
t 129
10.0%
u 107
8.3%
n 104
8.0%
r 89
6.9%
G 78
 
6.0%
o 62
 
4.8%
U 54
 
4.2%
Other values (7) 161
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 75343
83.2%
Uppercase Letter 12656
 
14.0%
Space Separator 2013
 
2.2%
Dash Punctuation 516
 
0.6%
ValueCountFrequency (%)
Lowercase Letter 1135
87.8%
Uppercase Letter 158
 
12.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 9226
12.2%
e 9095
12.1%
o 7976
10.6%
d 6618
8.8%
t 6549
8.7%
n 6044
8.0%
u 5131
6.8%
r 4095
 
5.4%
l 4039
 
5.4%
h 4026
 
5.3%
Other values (6) 12544
16.6%
ValueCountFrequency (%)
a 196
17.3%
e 177
15.6%
d 136
12.0%
t 129
11.4%
u 107
9.4%
n 104
9.2%
r 89
7.8%
o 62
 
5.5%
c 40
 
3.5%
l 30
 
2.6%
Other values (3) 65
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
G 3644
28.8%
U 3006
23.8%
S 2013
15.9%
H 2013
15.9%
C 1013
 
8.0%
P 516
 
4.1%
D 451
 
3.6%
ValueCountFrequency (%)
G 78
49.4%
U 54
34.2%
C 15
 
9.5%
D 11
 
7.0%
Space Separator
ValueCountFrequency (%)
2013
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 516
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 87999
97.2%
Common 2529
 
2.8%
ValueCountFrequency (%)
Latin 1293
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 9226
 
10.5%
e 9095
 
10.3%
o 7976
 
9.1%
d 6618
 
7.5%
t 6549
 
7.4%
n 6044
 
6.9%
u 5131
 
5.8%
r 4095
 
4.7%
l 4039
 
4.6%
h 4026
 
4.6%
Other values (13) 25200
28.6%
ValueCountFrequency (%)
a 196
15.2%
e 177
13.7%
d 136
10.5%
t 129
10.0%
u 107
8.3%
n 104
8.0%
r 89
6.9%
G 78
 
6.0%
o 62
 
4.8%
U 54
 
4.2%
Other values (7) 161
12.5%
Common
ValueCountFrequency (%)
2013
79.6%
- 516
 
20.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90528
100.0%
ValueCountFrequency (%)
ASCII 1293
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 9226
 
10.2%
e 9095
 
10.0%
o 7976
 
8.8%
d 6618
 
7.3%
t 6549
 
7.2%
n 6044
 
6.7%
u 5131
 
5.7%
r 4095
 
4.5%
l 4039
 
4.5%
h 4026
 
4.4%
Other values (15) 27729
30.6%
ValueCountFrequency (%)
a 196
15.2%
e 177
13.7%
d 136
10.5%
t 129
10.0%
u 107
8.3%
n 104
8.0%
r 89
6.9%
G 78
 
6.0%
o 62
 
4.8%
U 54
 
4.2%
Other values (7) 161
12.5%

Marital_Status
Categorical

 Profiling ReportTransformed Data
Distinct44
Distinct (%)< 0.1%2.5%
Missing00
Missing (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
Married
4687 
Single
3943 
Unknown
749 
Divorced
748 
Single
73 
Married
68 
Unknown
11 
Divorced
 
6

Length

 Profiling ReportTransformed Data
Max length88
Median length77.5
Mean length6.68450686.5759494
Min length66

Characters and Unicode

 Profiling ReportTransformed Data
Total characters676941039
Distinct characters1717
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling ReportTransformed Data
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling ReportTransformed Data
1st rowMarriedUnknown
2nd rowSingleMarried
3rd rowMarriedSingle
4th rowUnknownSingle
5th rowMarriedMarried

Common Values

ValueCountFrequency (%)
Married 4687
46.3%
Single 3943
38.9%
Unknown 749
 
7.4%
Divorced 748
 
7.4%
ValueCountFrequency (%)
Single 73
46.2%
Married 68
43.0%
Unknown 11
 
7.0%
Divorced 6
 
3.8%

Length

2023-11-09T11:55:13.839714image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report

2023-11-09T11:55:13.902854image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:13.981511image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
married 4687
46.3%
single 3943
38.9%
unknown 749
 
7.4%
divorced 748
 
7.4%
ValueCountFrequency (%)
single 73
46.2%
married 68
43.0%
unknown 11
 
7.0%
divorced 6
 
3.8%

Most occurring characters

ValueCountFrequency (%)
r 10122
15.0%
i 9378
13.9%
e 9378
13.9%
n 6190
9.1%
d 5435
8.0%
M 4687
6.9%
a 4687
6.9%
l 3943
 
5.8%
g 3943
 
5.8%
S 3943
 
5.8%
Other values (7) 5988
8.8%
ValueCountFrequency (%)
e 147
14.1%
i 147
14.1%
r 142
13.7%
n 106
10.2%
d 74
7.1%
S 73
7.0%
l 73
7.0%
g 73
7.0%
M 68
6.5%
a 68
6.5%
Other values (7) 68
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57567
85.0%
Uppercase Letter 10127
 
15.0%
ValueCountFrequency (%)
Lowercase Letter 881
84.8%
Uppercase Letter 158
 
15.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 10122
17.6%
i 9378
16.3%
e 9378
16.3%
n 6190
10.8%
d 5435
9.4%
a 4687
8.1%
l 3943
 
6.8%
g 3943
 
6.8%
o 1497
 
2.6%
k 749
 
1.3%
Other values (3) 2245
 
3.9%
ValueCountFrequency (%)
e 147
16.7%
i 147
16.7%
r 142
16.1%
n 106
12.0%
d 74
8.4%
l 73
8.3%
g 73
8.3%
a 68
7.7%
o 17
 
1.9%
k 11
 
1.2%
Other values (3) 23
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
M 4687
46.3%
S 3943
38.9%
U 749
 
7.4%
D 748
 
7.4%
ValueCountFrequency (%)
S 73
46.2%
M 68
43.0%
U 11
 
7.0%
D 6
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 67694
100.0%
ValueCountFrequency (%)
Latin 1039
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 10122
15.0%
i 9378
13.9%
e 9378
13.9%
n 6190
9.1%
d 5435
8.0%
M 4687
6.9%
a 4687
6.9%
l 3943
 
5.8%
g 3943
 
5.8%
S 3943
 
5.8%
Other values (7) 5988
8.8%
ValueCountFrequency (%)
e 147
14.1%
i 147
14.1%
r 142
13.7%
n 106
10.2%
d 74
7.1%
S 73
7.0%
l 73
7.0%
g 73
7.0%
M 68
6.5%
a 68
6.5%
Other values (7) 68
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67694
100.0%
ValueCountFrequency (%)
ASCII 1039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 10122
15.0%
i 9378
13.9%
e 9378
13.9%
n 6190
9.1%
d 5435
8.0%
M 4687
6.9%
a 4687
6.9%
l 3943
 
5.8%
g 3943
 
5.8%
S 3943
 
5.8%
Other values (7) 5988
8.8%
ValueCountFrequency (%)
e 147
14.1%
i 147
14.1%
r 142
13.7%
n 106
10.2%
d 74
7.1%
S 73
7.0%
l 73
7.0%
g 73
7.0%
M 68
6.5%
a 68
6.5%
Other values (7) 68
6.5%

Income_Category
Categorical

 Profiling ReportTransformed Data
Distinct66
Distinct (%)0.1%3.8%
Missing00
Missing (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
Less than $40K
3561 
$40K - $60K
1790 
$80K - $120K
1535 
$60K - $80K
1402 
Unknown
1112 
Less than $40K
51 
$40K - $60K
33 
$60K - $80K
30 
Unknown
22 
$80K - $120K
14 

Length

 Profiling ReportTransformed Data
Max length1414
Median length1212
Mean length11.48010311.297468
Min length77

Characters and Unicode

 Profiling ReportTransformed Data
Total characters1162591785
Distinct characters2222
Distinct categories77 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling ReportTransformed Data
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling ReportTransformed Data
1st row$60K - $80K$40K - $60K
2nd rowLess than $40KUnknown
3rd row$80K - $120K$40K - $60K
4th rowLess than $40KUnknown
5th row$60K - $80K$80K - $120K

Common Values

ValueCountFrequency (%)
Less than $40K 3561
35.2%
$40K - $60K 1790
17.7%
$80K - $120K 1535
15.2%
$60K - $80K 1402
 
13.8%
Unknown 1112
 
11.0%
$120K + 727
 
7.2%
ValueCountFrequency (%)
Less than $40K 51
32.3%
$40K - $60K 33
20.9%
$60K - $80K 30
19.0%
Unknown 22
13.9%
$80K - $120K 14
 
8.9%
$120K + 8
 
5.1%

Length

2023-11-09T11:55:14.059710image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report

2023-11-09T11:55:14.138416image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:14.248356image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
5454
19.9%
40k 5351
19.5%
less 3561
13.0%
than 3561
13.0%
60k 3192
11.6%
80k 2937
10.7%
120k 2262
8.2%
unknown 1112
 
4.1%
ValueCountFrequency (%)
85
20.1%
40k 84
19.9%
60k 63
14.9%
less 51
12.1%
than 51
12.1%
80k 44
10.4%
unknown 22
 
5.2%
120k 22
 
5.2%

Most occurring characters

ValueCountFrequency (%)
17303
14.9%
K 13742
11.8%
0 13742
11.8%
$ 13742
11.8%
s 7122
 
6.1%
n 6897
 
5.9%
4 5351
 
4.6%
- 4727
 
4.1%
e 3561
 
3.1%
L 3561
 
3.1%
Other values (12) 26511
22.8%
ValueCountFrequency (%)
264
14.8%
K 213
11.9%
0 213
11.9%
$ 213
11.9%
n 117
 
6.6%
s 102
 
5.7%
4 84
 
4.7%
- 77
 
4.3%
6 63
 
3.5%
e 51
 
2.9%
Other values (12) 388
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31599
27.2%
Decimal Number 29746
25.6%
Uppercase Letter 18415
15.8%
Space Separator 17303
14.9%
Currency Symbol 13742
11.8%
Dash Punctuation 4727
 
4.1%
Math Symbol 727
 
0.6%
ValueCountFrequency (%)
Lowercase Letter 489
27.4%
Decimal Number 448
25.1%
Uppercase Letter 286
16.0%
Space Separator 264
14.8%
Currency Symbol 213
11.9%
Dash Punctuation 77
 
4.3%
Math Symbol 8
 
0.4%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
17303
100.0%
ValueCountFrequency (%)
264
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 13742
74.6%
L 3561
 
19.3%
U 1112
 
6.0%
ValueCountFrequency (%)
K 213
74.5%
L 51
 
17.8%
U 22
 
7.7%
Decimal Number
ValueCountFrequency (%)
0 13742
46.2%
4 5351
 
18.0%
6 3192
 
10.7%
8 2937
 
9.9%
1 2262
 
7.6%
2 2262
 
7.6%
ValueCountFrequency (%)
0 213
47.5%
4 84
 
18.8%
6 63
 
14.1%
8 44
 
9.8%
1 22
 
4.9%
2 22
 
4.9%
Currency Symbol
ValueCountFrequency (%)
$ 13742
100.0%
ValueCountFrequency (%)
$ 213
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 7122
22.5%
n 6897
21.8%
e 3561
11.3%
a 3561
11.3%
h 3561
11.3%
t 3561
11.3%
k 1112
 
3.5%
o 1112
 
3.5%
w 1112
 
3.5%
ValueCountFrequency (%)
n 117
23.9%
s 102
20.9%
e 51
10.4%
a 51
10.4%
h 51
10.4%
t 51
10.4%
k 22
 
4.5%
o 22
 
4.5%
w 22
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 4727
100.0%
ValueCountFrequency (%)
- 77
100.0%
Math Symbol
ValueCountFrequency (%)
+ 727
100.0%
ValueCountFrequency (%)
+ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66245
57.0%
Latin 50014
43.0%
ValueCountFrequency (%)
Common 1010
56.6%
Latin 775
43.4%

Most frequent character per script

Common
ValueCountFrequency (%)
17303
26.1%
0 13742
20.7%
$ 13742
20.7%
4 5351
 
8.1%
- 4727
 
7.1%
6 3192
 
4.8%
8 2937
 
4.4%
1 2262
 
3.4%
2 2262
 
3.4%
+ 727
 
1.1%
ValueCountFrequency (%)
264
26.1%
0 213
21.1%
$ 213
21.1%
4 84
 
8.3%
- 77
 
7.6%
6 63
 
6.2%
8 44
 
4.4%
1 22
 
2.2%
2 22
 
2.2%
+ 8
 
0.8%
Latin
ValueCountFrequency (%)
K 13742
27.5%
s 7122
14.2%
n 6897
13.8%
e 3561
 
7.1%
L 3561
 
7.1%
a 3561
 
7.1%
h 3561
 
7.1%
t 3561
 
7.1%
U 1112
 
2.2%
k 1112
 
2.2%
Other values (2) 2224
 
4.4%
ValueCountFrequency (%)
K 213
27.5%
n 117
15.1%
s 102
13.2%
e 51
 
6.6%
L 51
 
6.6%
a 51
 
6.6%
h 51
 
6.6%
t 51
 
6.6%
U 22
 
2.8%
k 22
 
2.8%
Other values (2) 44
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 116259
100.0%
ValueCountFrequency (%)
ASCII 1785
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17303
14.9%
K 13742
11.8%
0 13742
11.8%
$ 13742
11.8%
s 7122
 
6.1%
n 6897
 
5.9%
4 5351
 
4.6%
- 4727
 
4.1%
e 3561
 
3.1%
L 3561
 
3.1%
Other values (12) 26511
22.8%
ValueCountFrequency (%)
264
14.8%
K 213
11.9%
0 213
11.9%
$ 213
11.9%
n 117
 
6.6%
s 102
 
5.7%
4 84
 
4.7%
- 77
 
4.3%
6 63
 
3.5%
e 51
 
2.9%
Other values (12) 388
21.7%

Card_Category
Categorical

 Profiling ReportTransformed Data
Distinct41
Distinct (%)< 0.1%0.6%
Missing00
Missing (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
Blue
9436 
Silver
 
555
Gold
 
116
Platinum
 
20
Blue
158 

Length

 Profiling ReportTransformed Data
Max length84
Median length44
Mean length4.11750774
Min length44

Characters and Unicode

 Profiling ReportTransformed Data
Total characters41698632
Distinct characters164
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling ReportTransformed Data
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling ReportTransformed Data
1st rowBlueBlue
2nd rowBlueBlue
3rd rowBlueBlue
4th rowBlueBlue
5th rowBlueBlue

Common Values

ValueCountFrequency (%)
Blue 9436
93.2%
Silver 555
 
5.5%
Gold 116
 
1.1%
Platinum 20
 
0.2%
ValueCountFrequency (%)
Blue 158
100.0%

Length

2023-11-09T11:55:14.346983image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report

2023-11-09T11:55:14.412271image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:14.474206image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
blue 9436
93.2%
silver 555
 
5.5%
gold 116
 
1.1%
platinum 20
 
0.2%
ValueCountFrequency (%)
blue 158
100.0%

Most occurring characters

ValueCountFrequency (%)
l 10127
24.3%
e 9991
24.0%
u 9456
22.7%
B 9436
22.6%
i 575
 
1.4%
S 555
 
1.3%
v 555
 
1.3%
r 555
 
1.3%
G 116
 
0.3%
o 116
 
0.3%
Other values (6) 216
 
0.5%
ValueCountFrequency (%)
B 158
25.0%
l 158
25.0%
u 158
25.0%
e 158
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31571
75.7%
Uppercase Letter 10127
 
24.3%
ValueCountFrequency (%)
Lowercase Letter 474
75.0%
Uppercase Letter 158
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 10127
32.1%
e 9991
31.6%
u 9456
30.0%
i 575
 
1.8%
v 555
 
1.8%
r 555
 
1.8%
o 116
 
0.4%
d 116
 
0.4%
a 20
 
0.1%
t 20
 
0.1%
Other values (2) 40
 
0.1%
ValueCountFrequency (%)
l 158
33.3%
u 158
33.3%
e 158
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 9436
93.2%
S 555
 
5.5%
G 116
 
1.1%
P 20
 
0.2%
ValueCountFrequency (%)
B 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41698
100.0%
ValueCountFrequency (%)
Latin 632
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 10127
24.3%
e 9991
24.0%
u 9456
22.7%
B 9436
22.6%
i 575
 
1.4%
S 555
 
1.3%
v 555
 
1.3%
r 555
 
1.3%
G 116
 
0.3%
o 116
 
0.3%
Other values (6) 216
 
0.5%
ValueCountFrequency (%)
B 158
25.0%
l 158
25.0%
u 158
25.0%
e 158
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41698
100.0%
ValueCountFrequency (%)
ASCII 632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 10127
24.3%
e 9991
24.0%
u 9456
22.7%
B 9436
22.6%
i 575
 
1.4%
S 555
 
1.3%
v 555
 
1.3%
r 555
 
1.3%
G 116
 
0.3%
o 116
 
0.3%
Other values (6) 216
 
0.5%
ValueCountFrequency (%)
B 158
25.0%
l 158
25.0%
u 158
25.0%
e 158
25.0%

Months_on_book
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct4434
Distinct (%)0.4%21.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean35.92840937.563291
 Profiling ReportTransformed Data
Minimum1313
Maximum5656
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:14.553416image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum1313
5-th percentile2224.85
Q13133
median3636
Q34042
95-th percentile5051
Maximum5656
Range4343
Interquartile range (IQR)99

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation7.98641638.040846
Coefficient of variation (CV)0.222286950.21406128
Kurtosis0.400100120.24368305
Mean35.92840937.563291
Median Absolute Deviation (MAD)45
Skewness-0.10656536-0.0011778359
Sum3638475935
Variance63.78284664.655204
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:14.663180image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36 2463
24.3%
37 358
 
3.5%
34 353
 
3.5%
38 347
 
3.4%
39 341
 
3.4%
40 333
 
3.3%
31 318
 
3.1%
35 317
 
3.1%
33 305
 
3.0%
30 300
 
3.0%
Other values (34) 4692
46.3%
ValueCountFrequency (%)
36 30
19.0%
40 10
 
6.3%
41 10
 
6.3%
46 8
 
5.1%
35 8
 
5.1%
39 7
 
4.4%
43 6
 
3.8%
32 6
 
3.8%
28 6
 
3.8%
33 5
 
3.2%
Other values (24) 62
39.2%
ValueCountFrequency (%)
13 70
0.7%
14 16
 
0.2%
15 34
 
0.3%
16 29
 
0.3%
17 39
 
0.4%
18 58
0.6%
19 63
0.6%
20 74
0.7%
21 83
0.8%
22 105
1.0%
ValueCountFrequency (%)
13 1
 
0.6%
19 1
 
0.6%
20 1
 
0.6%
22 4
2.5%
24 1
 
0.6%
25 2
 
1.3%
26 3
1.9%
27 3
1.9%
28 6
3.8%
29 4
2.5%
ValueCountFrequency (%)
13 1
 
< 0.1%
19 1
 
< 0.1%
20 1
 
< 0.1%
22 4
< 0.1%
24 1
 
< 0.1%
25 2
 
< 0.1%
26 3
< 0.1%
27 3
< 0.1%
28 6
0.1%
29 4
< 0.1%
ValueCountFrequency (%)
13 70
44.3%
14 16
 
10.1%
15 34
 
21.5%
16 29
 
18.4%
17 39
 
24.7%
18 58
36.7%
19 63
39.9%
20 74
46.8%
21 83
52.5%
22 105
66.5%

Total_Relationship_Count
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct63
Distinct (%)0.1%1.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean3.81258023.0759494
 Profiling ReportTransformed Data
Minimum12
Maximum64
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:14.741719image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum12
5-th percentile12
Q133
median43
Q354
95-th percentile64
Maximum64
Range52
Interquartile range (IQR)21

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation1.55440790.74478487
Coefficient of variation (CV)0.407704960.24213171
Kurtosis-1.0061305-1.1788354
Mean3.81258023.0759494
Median Absolute Deviation (MAD)11
Skewness-0.16245241-0.12354842
Sum38610486
Variance2.41618380.55470451
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:14.804647image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2305
22.8%
4 1912
18.9%
5 1891
18.7%
6 1866
18.4%
2 1243
12.3%
1 910
 
9.0%
ValueCountFrequency (%)
3 70
44.3%
4 50
31.6%
2 38
24.1%
ValueCountFrequency (%)
1 910
 
9.0%
2 1243
12.3%
3 2305
22.8%
4 1912
18.9%
5 1891
18.7%
6 1866
18.4%
ValueCountFrequency (%)
2 38
24.1%
3 70
44.3%
4 50
31.6%
ValueCountFrequency (%)
2 38
0.4%
3 70
0.7%
4 50
0.5%
ValueCountFrequency (%)
1 910
 
575.9%
2 1243
786.7%
3 2305
1458.9%
4 1912
1210.1%
5 1891
1196.8%
6 1866
1181.0%

Months_Inactive_12_mon
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct76
Distinct (%)0.1%3.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.34116722.4367089
 Profiling ReportTransformed Data
Minimum01
Maximum66
Zeros290
Zeros (%)0.3%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:14.875655image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum01
5-th percentile11
Q122
median22
Q333
95-th percentile44.15
Maximum66
Range65
Interquartile range (IQR)11

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation1.01062241.1083559
Coefficient of variation (CV)0.43167460.45485774
Kurtosis1.09852261.8342674
Mean2.34116722.4367089
Median Absolute Deviation (MAD)11
Skewness0.633061131.0004781
Sum23709385
Variance1.02135761.2284528
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:14.952811image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 3846
38.0%
2 3282
32.4%
1 2233
22.0%
4 435
 
4.3%
5 178
 
1.8%
6 124
 
1.2%
0 29
 
0.3%
ValueCountFrequency (%)
3 60
38.0%
2 52
32.9%
1 32
20.3%
4 6
 
3.8%
6 5
 
3.2%
5 3
 
1.9%
ValueCountFrequency (%)
0 29
 
0.3%
1 2233
22.0%
2 3282
32.4%
3 3846
38.0%
4 435
 
4.3%
5 178
 
1.8%
6 124
 
1.2%
ValueCountFrequency (%)
1 32
20.3%
2 52
32.9%
3 60
38.0%
4 6
 
3.8%
5 3
 
1.9%
6 5
 
3.2%
ValueCountFrequency (%)
1 32
0.3%
2 52
0.5%
3 60
0.6%
4 6
 
0.1%
5 3
 
< 0.1%
6 5
 
< 0.1%
ValueCountFrequency (%)
0 29
 
18.4%
1 2233
1413.3%
2 3282
2077.2%
3 3846
2434.2%
4 435
 
275.3%
5 178
 
112.7%
6 124
 
78.5%

Contacts_Count_12_mon
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct76
Distinct (%)0.1%3.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.45531752.4746835
 Profiling ReportTransformed Data
Minimum00
Maximum65
Zeros39910
Zeros (%)3.9%6.3%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:15.015878image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum00
5-th percentile10
Q122
median23
Q333
95-th percentile44
Maximum65
Range65
Interquartile range (IQR)11

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation1.10622511.1269674
Coefficient of variation (CV)0.450542610.45539861
Kurtosis0.00086265663-0.23726594
Mean2.45531752.4746835
Median Absolute Deviation (MAD)11
Skewness0.011005626-0.42300737
Sum24865391
Variance1.22373411.2700556
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:15.235830image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 3380
33.4%
2 3227
31.9%
1 1499
14.8%
4 1392
13.7%
0 399
 
3.9%
5 176
 
1.7%
6 54
 
0.5%
ValueCountFrequency (%)
3 61
38.6%
2 41
25.9%
4 24
 
15.2%
1 20
 
12.7%
0 10
 
6.3%
5 2
 
1.3%
ValueCountFrequency (%)
0 399
 
3.9%
1 1499
14.8%
2 3227
31.9%
3 3380
33.4%
4 1392
13.7%
5 176
 
1.7%
6 54
 
0.5%
ValueCountFrequency (%)
0 10
 
6.3%
1 20
 
12.7%
2 41
25.9%
3 61
38.6%
4 24
 
15.2%
5 2
 
1.3%
ValueCountFrequency (%)
0 10
 
0.1%
1 20
 
0.2%
2 41
0.4%
3 61
0.6%
4 24
 
0.2%
5 2
 
< 0.1%
ValueCountFrequency (%)
0 399
 
252.5%
1 1499
948.7%
2 3227
2042.4%
3 3380
2139.2%
4 1392
881.0%
5 176
 
111.4%
6 54
 
34.2%

Credit_Limit
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct6205157
Distinct (%)61.3%99.4%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean8631.95375913.6392
 Profiling ReportTransformed Data
Minimum1438.33521
Maximum345169397
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:15.345764image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum1438.33521
5-th percentile1438.513658.35
Q125554216
median45495614.5
Q311067.57319.25
95-th percentile345168995.6
Maximum345169397
Range33077.75876
Interquartile range (IQR)8512.53103.25

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation9088.77671793.0355
Coefficient of variation (CV)1.05292230.3032034
Kurtosis1.8089893-1.1847606
Mean8631.95375913.6392
Median Absolute Deviation (MAD)25931500.5
Skewness1.66672580.36928355
Sum87415795934355
Variance826058613214976.3
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:15.461683image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34516 508
 
5.0%
1438.3 507
 
5.0%
9959 18
 
0.2%
15987 18
 
0.2%
23981 12
 
0.1%
2490 11
 
0.1%
6224 11
 
0.1%
3735 11
 
0.1%
7469 10
 
0.1%
2069 8
 
0.1%
Other values (6195) 9013
89.0%
ValueCountFrequency (%)
7169 2
 
1.3%
3672 1
 
0.6%
4170 1
 
0.6%
7106 1
 
0.6%
7603 1
 
0.6%
3805 1
 
0.6%
5716 1
 
0.6%
4576 1
 
0.6%
3861 1
 
0.6%
3649 1
 
0.6%
Other values (147) 147
93.0%
ValueCountFrequency (%)
1438.3 507
5.0%
1439 2
 
< 0.1%
1440 1
 
< 0.1%
1441 2
 
< 0.1%
1442 1
 
< 0.1%
1443 3
 
< 0.1%
1446 1
 
< 0.1%
1449 2
 
< 0.1%
1451 2
 
< 0.1%
1452 2
 
< 0.1%
ValueCountFrequency (%)
3521 1
0.6%
3532 1
0.6%
3540 1
0.6%
3585 1
0.6%
3626 1
0.6%
3640 1
0.6%
3642 1
0.6%
3649 1
0.6%
3660 1
0.6%
3667 1
0.6%
ValueCountFrequency (%)
3521 1
< 0.1%
3532 1
< 0.1%
3540 1
< 0.1%
3585 1
< 0.1%
3626 1
< 0.1%
3640 1
< 0.1%
3642 1
< 0.1%
3649 1
< 0.1%
3660 1
< 0.1%
3667 1
< 0.1%
ValueCountFrequency (%)
1438.3 507
320.9%
1439 2
 
1.3%
1440 1
 
0.6%
1441 2
 
1.3%
1442 1
 
0.6%
1443 3
 
1.9%
1446 1
 
0.6%
1449 2
 
1.3%
1451 2
 
1.3%
1452 2
 
1.3%

Total_Revolving_Bal
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct1974132
Distinct (%)19.5%83.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1162.8141763.06329
 Profiling ReportTransformed Data
Minimum0145
Maximum2517996
Zeros24700
Zeros (%)24.4%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:15.587786image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum0145
5-th percentile0408
Q1359662.25
median1276794
Q31784911.25
95-th percentile2517981.6
Maximum2517996
Range2517851
Interquartile range (IQR)1425249

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation814.98734182.1388
Coefficient of variation (CV)0.700875030.23869423
Kurtosis-1.14599181.2491673
Mean1162.8141763.06329
Median Absolute Deviation (MAD)591121
Skewness-0.14883725-1.0813498
Sum11775818120564
Variance664204.3633174.544
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:15.713438image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2470
 
24.4%
2517 508
 
5.0%
1965 12
 
0.1%
1480 12
 
0.1%
1434 11
 
0.1%
1664 11
 
0.1%
1720 11
 
0.1%
1590 10
 
0.1%
1542 10
 
0.1%
1528 10
 
0.1%
Other values (1964) 7062
69.7%
ValueCountFrequency (%)
795 3
 
1.9%
622 3
 
1.9%
719 2
 
1.3%
915 2
 
1.3%
847 2
 
1.3%
561 2
 
1.3%
688 2
 
1.3%
938 2
 
1.3%
947 2
 
1.3%
961 2
 
1.3%
Other values (122) 136
86.1%
ValueCountFrequency (%)
0 2470
24.4%
132 1
 
< 0.1%
134 1
 
< 0.1%
145 1
 
< 0.1%
154 1
 
< 0.1%
157 1
 
< 0.1%
159 2
 
< 0.1%
168 2
 
< 0.1%
170 1
 
< 0.1%
186 1
 
< 0.1%
ValueCountFrequency (%)
145 1
0.6%
193 1
0.6%
211 1
0.6%
232 1
0.6%
274 1
0.6%
317 1
0.6%
318 1
0.6%
357 1
0.6%
417 1
0.6%
468 1
0.6%
ValueCountFrequency (%)
145 1
< 0.1%
193 1
< 0.1%
211 1
< 0.1%
232 1
< 0.1%
274 1
< 0.1%
317 1
< 0.1%
318 1
< 0.1%
357 1
< 0.1%
417 1
< 0.1%
468 1
< 0.1%
ValueCountFrequency (%)
0 2470
1563.3%
132 1
 
0.6%
134 1
 
0.6%
145 1
 
0.6%
154 1
 
0.6%
157 1
 
0.6%
159 2
 
1.3%
168 2
 
1.3%
170 1
 
0.6%
186 1
 
0.6%

Avg_Open_To_Buy
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct6813155
Distinct (%)67.3%98.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean7469.13965150.5759
 Profiling ReportTransformed Data
Minimum32654
Maximum345168959
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:15.839025image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum32654
5-th percentile480.32846.3
Q11324.53501.5
median34744892.5
Q398596528.75
95-th percentile32183.48203.15
Maximum345168959
Range345136305
Interquartile range (IQR)8534.53027.25

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation9090.68531790.2754
Coefficient of variation (CV)1.21709940.34758742
Kurtosis1.7986173-1.1267665
Mean7469.13965150.5759
Median Absolute Deviation (MAD)26651450.5
Skewness1.66169650.3762689
Sum75639977813791
Variance826405603205086
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:15.955322image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438.3 324
 
3.2%
34516 98
 
1.0%
31999 26
 
0.3%
787 8
 
0.1%
701 7
 
0.1%
713 7
 
0.1%
953 7
 
0.1%
463 7
 
0.1%
990 6
 
0.1%
788 6
 
0.1%
Other values (6803) 9631
95.1%
ValueCountFrequency (%)
3495 2
 
1.3%
2732 2
 
1.3%
6014 2
 
1.3%
8081 1
 
0.6%
6859 1
 
0.6%
2984 1
 
0.6%
5093 1
 
0.6%
4383 1
 
0.6%
3239 1
 
0.6%
2720 1
 
0.6%
Other values (145) 145
91.8%
ValueCountFrequency (%)
3 1
< 0.1%
10 1
< 0.1%
14 2
< 0.1%
15 1
< 0.1%
24 1
< 0.1%
28 1
< 0.1%
29 1
< 0.1%
36 1
< 0.1%
39 2
< 0.1%
41 2
< 0.1%
ValueCountFrequency (%)
2654 1
0.6%
2691 1
0.6%
2720 1
0.6%
2732 2
1.3%
2768 1
0.6%
2786 1
0.6%
2831 1
0.6%
2849 1
0.6%
2858 1
0.6%
2862 1
0.6%
ValueCountFrequency (%)
2654 1
< 0.1%
2691 1
< 0.1%
2720 1
< 0.1%
2732 2
< 0.1%
2768 1
< 0.1%
2786 1
< 0.1%
2831 1
< 0.1%
2849 1
< 0.1%
2858 1
< 0.1%
2862 1
< 0.1%
ValueCountFrequency (%)
3 1
0.6%
10 1
0.6%
14 2
1.3%
15 1
0.6%
24 1
0.6%
28 1
0.6%
29 1
0.6%
36 1
0.6%
39 2
1.3%
41 2
1.3%

Total_Amt_Chng_Q4_Q1
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct1158142
Distinct (%)11.4%89.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.759940650.77031646
 Profiling ReportTransformed Data
Minimum00.432
Maximum3.3972.275
Zeros50
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:16.081214image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum00.432
5-th percentile0.4630.50655
Q10.6310.64775
median0.7360.7505
Q30.8590.85575
95-th percentile1.1031.0435
Maximum3.3972.275
Range3.3971.843
Interquartile range (IQR)0.2280.208

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation0.219206770.21401101
Coefficient of variation (CV)0.288452480.2778222
Kurtosis9.993501216.530341
Mean0.759940650.77031646
Median Absolute Deviation (MAD)0.1140.1035
Skewness1.73206342.8231936
Sum7695.919121.71
Variance0.0480516080.045800715
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:16.206853image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.791 36
 
0.4%
0.712 34
 
0.3%
0.743 34
 
0.3%
0.718 33
 
0.3%
0.735 33
 
0.3%
0.744 32
 
0.3%
0.699 32
 
0.3%
0.722 32
 
0.3%
0.731 31
 
0.3%
0.631 31
 
0.3%
Other values (1148) 9799
96.8%
ValueCountFrequency (%)
0.647 3
 
1.9%
0.765 3
 
1.9%
0.815 2
 
1.3%
0.807 2
 
1.3%
0.681 2
 
1.3%
0.65 2
 
1.3%
0.676 2
 
1.3%
0.711 2
 
1.3%
0.85 2
 
1.3%
0.958 2
 
1.3%
Other values (132) 136
86.1%
ValueCountFrequency (%)
0 5
< 0.1%
0.01 1
 
< 0.1%
0.018 1
 
< 0.1%
0.046 1
 
< 0.1%
0.061 2
 
< 0.1%
0.072 1
 
< 0.1%
0.101 1
 
< 0.1%
0.12 1
 
< 0.1%
0.153 1
 
< 0.1%
0.163 1
 
< 0.1%
ValueCountFrequency (%)
0.432 1
0.6%
0.456 1
0.6%
0.469 1
0.6%
0.471 1
0.6%
0.475 1
0.6%
0.485 1
0.6%
0.504 2
1.3%
0.507 1
0.6%
0.508 1
0.6%
0.511 1
0.6%
ValueCountFrequency (%)
0.432 1
< 0.1%
0.456 1
< 0.1%
0.469 1
< 0.1%
0.471 1
< 0.1%
0.475 1
< 0.1%
0.485 1
< 0.1%
0.504 2
< 0.1%
0.507 1
< 0.1%
0.508 1
< 0.1%
0.511 1
< 0.1%
ValueCountFrequency (%)
0 5
3.2%
0.01 1
 
0.6%
0.018 1
 
0.6%
0.046 1
 
0.6%
0.061 2
 
1.3%
0.072 1
 
0.6%
0.101 1
 
0.6%
0.12 1
 
0.6%
0.153 1
 
0.6%
0.163 1
 
0.6%

Total_Trans_Amt
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct5033153
Distinct (%)49.7%96.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4404.08634772.4684
 Profiling ReportTransformed Data
Minimum510791
Maximum1848416737
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:16.332250image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum510791
5-th percentile1283.31346.5
Q12155.52456.25
median38993945.5
Q347414857
95-th percentile1421214604.25
Maximum1848416737
Range1797415946
Interquartile range (IQR)2585.52400.75

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation3397.12933778.2852
Coefficient of variation (CV)0.771358470.79168365
Kurtosis3.89402342.7259701
Mean4404.08634772.4684
Median Absolute Deviation (MAD)13081268
Skewness2.04100341.8761048
Sum44600182754050
Variance1154048714275439
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:16.466559image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4253 11
 
0.1%
4509 11
 
0.1%
4518 10
 
0.1%
2229 10
 
0.1%
4220 9
 
0.1%
4869 9
 
0.1%
4037 9
 
0.1%
4313 9
 
0.1%
4498 9
 
0.1%
4042 9
 
0.1%
Other values (5023) 10031
99.1%
ValueCountFrequency (%)
3964 2
 
1.3%
4399 2
 
1.3%
4828 2
 
1.3%
14596 2
 
1.3%
1193 2
 
1.3%
4283 1
 
0.6%
5192 1
 
0.6%
2497 1
 
0.6%
4326 1
 
0.6%
4387 1
 
0.6%
Other values (143) 143
90.5%
ValueCountFrequency (%)
510 1
< 0.1%
530 1
< 0.1%
563 1
< 0.1%
569 1
< 0.1%
594 1
< 0.1%
596 1
< 0.1%
597 1
< 0.1%
602 1
< 0.1%
615 1
< 0.1%
643 1
< 0.1%
ValueCountFrequency (%)
791 1
0.6%
842 1
0.6%
870 1
0.6%
990 1
0.6%
1165 1
0.6%
1193 2
1.3%
1321 1
0.6%
1351 1
0.6%
1359 1
0.6%
1438 1
0.6%
ValueCountFrequency (%)
791 1
< 0.1%
842 1
< 0.1%
870 1
< 0.1%
990 1
< 0.1%
1165 1
< 0.1%
1193 2
< 0.1%
1321 1
< 0.1%
1351 1
< 0.1%
1359 1
< 0.1%
1438 1
< 0.1%
ValueCountFrequency (%)
510 1
0.6%
530 1
0.6%
563 1
0.6%
569 1
0.6%
594 1
0.6%
596 1
0.6%
597 1
0.6%
602 1
0.6%
615 1
0.6%
643 1
0.6%

Total_Trans_Ct
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct12672
Distinct (%)1.2%45.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean64.85869567.746835
 Profiling ReportTransformed Data
Minimum1022
Maximum139123
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:16.583571image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum1022
5-th percentile2828
Q14549.25
median6770
Q38181
95-th percentile105105.6
Maximum139123
Range129101
Interquartile range (IQR)3631.75

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation23.4725723.477306
Coefficient of variation (CV)0.361903220.34654469
Kurtosis-0.36716324-0.4133794
Mean64.85869567.746835
Median Absolute Deviation (MAD)1715.5
Skewness0.153673070.052535701
Sum65682410704
Variance550.96156551.18391
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:16.709237image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
81 208
 
2.1%
71 203
 
2.0%
75 203
 
2.0%
69 202
 
2.0%
82 202
 
2.0%
76 198
 
2.0%
77 197
 
1.9%
70 193
 
1.9%
74 190
 
1.9%
78 190
 
1.9%
Other values (116) 8141
80.4%
ValueCountFrequency (%)
77 8
 
5.1%
79 5
 
3.2%
59 5
 
3.2%
81 5
 
3.2%
67 4
 
2.5%
38 4
 
2.5%
76 4
 
2.5%
70 4
 
2.5%
82 4
 
2.5%
78 4
 
2.5%
Other values (62) 111
70.3%
ValueCountFrequency (%)
10 4
 
< 0.1%
11 2
 
< 0.1%
12 4
 
< 0.1%
13 5
 
< 0.1%
14 9
 
0.1%
15 16
0.2%
16 13
0.1%
17 13
0.1%
18 23
0.2%
19 11
0.1%
ValueCountFrequency (%)
22 2
1.3%
24 2
1.3%
25 1
 
0.6%
26 1
 
0.6%
27 1
 
0.6%
28 2
1.3%
30 1
 
0.6%
31 2
1.3%
34 2
1.3%
35 4
2.5%
ValueCountFrequency (%)
22 2
< 0.1%
24 2
< 0.1%
25 1
 
< 0.1%
26 1
 
< 0.1%
27 1
 
< 0.1%
28 2
< 0.1%
30 1
 
< 0.1%
31 2
< 0.1%
34 2
< 0.1%
35 4
< 0.1%
ValueCountFrequency (%)
10 4
 
2.5%
11 2
 
1.3%
12 4
 
2.5%
13 5
 
3.2%
14 9
 
5.7%
15 16
10.1%
16 13
8.2%
17 13
8.2%
18 23
14.6%
19 11
7.0%

Total_Ct_Chng_Q4_Q1
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct830126
Distinct (%)8.2%79.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.712222380.69213291
 Profiling ReportTransformed Data
Minimum00.231
Maximum3.7141.5
Zeros70
Zeros (%)0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:16.834828image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum00.231
5-th percentile0.3680.37125
Q10.5820.5795
median0.7020.669
Q30.8180.78825
95-th percentile1.0691.083
Maximum3.7141.5
Range3.7141.269
Interquartile range (IQR)0.2360.20875

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation0.238086090.20818176
Coefficient of variation (CV)0.334286170.30078292
Kurtosis15.6892932.0395173
Mean0.712222380.69213291
Median Absolute Deviation (MAD)0.1190.099
Skewness2.06403060.84649393
Sum7212.676109.357
Variance0.0566849870.043339645
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:16.960205image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.667 171
 
1.7%
1 166
 
1.6%
0.5 161
 
1.6%
0.75 156
 
1.5%
0.6 113
 
1.1%
0.8 101
 
1.0%
0.714 92
 
0.9%
0.833 85
 
0.8%
0.778 69
 
0.7%
0.625 63
 
0.6%
Other values (820) 8950
88.4%
ValueCountFrequency (%)
0.694 3
 
1.9%
0.75 3
 
1.9%
0.64 3
 
1.9%
0.581 3
 
1.9%
0.667 3
 
1.9%
0.733 3
 
1.9%
0.652 3
 
1.9%
0.723 3
 
1.9%
0.556 2
 
1.3%
0.757 2
 
1.3%
Other values (116) 130
82.3%
ValueCountFrequency (%)
0 7
0.1%
0.028 1
 
< 0.1%
0.029 1
 
< 0.1%
0.038 1
 
< 0.1%
0.053 1
 
< 0.1%
0.059 2
 
< 0.1%
0.062 1
 
< 0.1%
0.074 1
 
< 0.1%
0.077 3
< 0.1%
0.091 3
< 0.1%
ValueCountFrequency (%)
0.231 1
0.6%
0.273 1
0.6%
0.29 1
0.6%
0.3 1
0.6%
0.308 1
0.6%
0.333 1
0.6%
0.346 1
0.6%
0.35 1
0.6%
0.375 1
0.6%
0.4 2
1.3%
ValueCountFrequency (%)
0.231 1
< 0.1%
0.273 1
< 0.1%
0.29 1
< 0.1%
0.3 1
< 0.1%
0.308 1
< 0.1%
0.333 1
< 0.1%
0.346 1
< 0.1%
0.35 1
< 0.1%
0.375 1
< 0.1%
0.4 2
< 0.1%
ValueCountFrequency (%)
0 7
4.4%
0.028 1
 
0.6%
0.029 1
 
0.6%
0.038 1
 
0.6%
0.053 1
 
0.6%
0.059 2
 
1.3%
0.062 1
 
0.6%
0.074 1
 
0.6%
0.077 3
1.9%
0.091 3
1.9%

Avg_Utilization_Ratio
Real number (ℝ)

 Profiling ReportTransformed Data
Distinct964108
Distinct (%)9.5%68.4%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.274893550.14063924
 Profiling ReportTransformed Data
Minimum00.016
Maximum0.9990.267
Zeros24700
Zeros (%)24.4%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:17.079916image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum00.016
5-th percentile00.061
Q10.0230.10225
median0.1760.1355
Q30.5030.181
95-th percentile0.7930.2353
Maximum0.9990.267
Range0.9990.251
Interquartile range (IQR)0.480.07875

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation0.275691470.05241204
Coefficient of variation (CV)1.00290260.3726701
Kurtosis-0.79497195-0.45011028
Mean0.274893550.14063924
Median Absolute Deviation (MAD)0.1760.039
Skewness0.7180080.24741803
Sum2783.84722.221
Variance0.0760057860.0027470219
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:17.203518image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2470
 
24.4%
0.073 44
 
0.4%
0.057 33
 
0.3%
0.048 32
 
0.3%
0.06 30
 
0.3%
0.061 29
 
0.3%
0.045 29
 
0.3%
0.059 28
 
0.3%
0.069 28
 
0.3%
0.053 27
 
0.3%
Other values (954) 7377
72.8%
ValueCountFrequency (%)
0.126 4
 
2.5%
0.158 4
 
2.5%
0.186 3
 
1.9%
0.216 3
 
1.9%
0.189 3
 
1.9%
0.191 3
 
1.9%
0.104 3
 
1.9%
0.144 3
 
1.9%
0.122 3
 
1.9%
0.195 3
 
1.9%
Other values (98) 126
79.7%
ValueCountFrequency (%)
0 2470
24.4%
0.004 1
 
< 0.1%
0.005 1
 
< 0.1%
0.006 3
 
< 0.1%
0.007 1
 
< 0.1%
0.008 2
 
< 0.1%
0.009 1
 
< 0.1%
0.01 1
 
< 0.1%
0.011 1
 
< 0.1%
0.012 4
 
< 0.1%
ValueCountFrequency (%)
0.016 1
0.6%
0.039 1
0.6%
0.04 1
0.6%
0.042 1
0.6%
0.05 1
0.6%
0.053 1
0.6%
0.055 1
0.6%
0.061 2
1.3%
0.063 1
0.6%
0.067 1
0.6%
ValueCountFrequency (%)
0.016 1
< 0.1%
0.039 1
< 0.1%
0.04 1
< 0.1%
0.042 1
< 0.1%
0.05 1
< 0.1%
0.053 1
< 0.1%
0.055 1
< 0.1%
0.061 2
< 0.1%
0.063 1
< 0.1%
0.067 1
< 0.1%
ValueCountFrequency (%)
0 2470
1563.3%
0.004 1
 
0.6%
0.005 1
 
0.6%
0.006 3
 
1.9%
0.007 1
 
0.6%
0.008 2
 
1.3%
0.009 1
 
0.6%
0.01 1
 
0.6%
0.011 1
 
0.6%
0.012 4
 
2.5%
 Profiling ReportTransformed Data
Distinct1704123
Distinct (%)16.8%77.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.159997460.1955359
 Profiling ReportTransformed Data
Minimum7.6642 × 10-62.0889 × 10-5
Maximum0.999580.99893
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:17.329105image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum7.6642 × 10-62.0889 × 10-5
5-th percentile4.2358 × 10-53.58496 × 10-5
Q19.8983 × 10-59.350925 × 10-5
median0.000181460.00019864
Q30.00033730.00050046
95-th percentile0.996970.9971765
Maximum0.999580.99893
Range0.999572340.99890911
Interquartile range (IQR)0.0002383170.00040695075

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation0.365301010.39663583
Coefficient of variation (CV)2.28316752.0284552
Kurtosis1.41753520.39098319
Mean0.159997460.1955359
Median Absolute Deviation (MAD)0.0001102340.000127414
Skewness1.84853841.5447176
Sum1620.294330.894673
Variance0.133444830.15731998
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:17.602326image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00019864 80
 
0.8%
0.0003139 78
 
0.8%
0.00030251 77
 
0.8%
0.00018665 73
 
0.7%
0.00011382 71
 
0.7%
0.00019143 66
 
0.7%
0.00011811 66
 
0.7%
0.00017987 63
 
0.6%
0.00018145 60
 
0.6%
0.00016883 59
 
0.6%
Other values (1694) 9434
93.2%
ValueCountFrequency (%)
0.00019864 5
 
3.2%
0.00018665 4
 
2.5%
0.99499 4
 
2.5%
0.00031104 3
 
1.9%
0.00017987 3
 
1.9%
0.99683 3
 
1.9%
0.00011382 3
 
1.9%
7.1226 × 10-52
 
1.3%
0.00011937 2
 
1.3%
4.7263 × 10-52
 
1.3%
Other values (113) 127
80.4%
ValueCountFrequency (%)
7.6642 × 10-61
< 0.1%
7.7559 × 10-61
< 0.1%
1.0252 × 10-51
< 0.1%
1.0546 × 10-51
< 0.1%
1.1536 × 10-51
< 0.1%
1.4461 × 10-51
< 0.1%
1.6948 × 10-51
< 0.1%
1.6949 × 10-51
< 0.1%
1.7434 × 10-52
< 0.1%
1.7785 × 10-51
< 0.1%
ValueCountFrequency (%)
2.0889 × 10-51
0.6%
2.1081 × 10-51
0.6%
2.2331 × 10-51
0.6%
3.1176 × 10-52
1.3%
3.3214 × 10-52
1.3%
3.4833 × 10-51
0.6%
3.6029 × 10-51
0.6%
4.3568 × 10-51
0.6%
4.7263 × 10-52
1.3%
5.1697 × 10-51
0.6%
ValueCountFrequency (%)
2.0889 × 10-51
< 0.1%
2.1081 × 10-51
< 0.1%
2.2331 × 10-51
< 0.1%
3.1176 × 10-52
< 0.1%
3.3214 × 10-52
< 0.1%
3.4833 × 10-51
< 0.1%
3.6029 × 10-51
< 0.1%
4.3568 × 10-51
< 0.1%
4.7263 × 10-52
< 0.1%
5.1697 × 10-51
< 0.1%
ValueCountFrequency (%)
7.6642 × 10-61
0.6%
7.7559 × 10-61
0.6%
1.0252 × 10-51
0.6%
1.0546 × 10-51
0.6%
1.1536 × 10-51
0.6%
1.4461 × 10-51
0.6%
1.6948 × 10-51
0.6%
1.6949 × 10-51
0.6%
1.7434 × 10-52
1.3%
1.7785 × 10-51
0.6%
 Profiling ReportTransformed Data
Distinct64069
Distinct (%)6.3%43.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.840002570.80446381
 Profiling ReportTransformed Data
Minimum0.000419980.00106612
Maximum0.999990.99998
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size79.2 KiB2.5 KiB
2023-11-09T11:55:17.727932image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

 Profiling ReportTransformed Data
Minimum0.000419980.00106612
5-th percentile0.003025460.0028257355
Q10.999660.9994975
median0.999820.9998
Q30.99990.9999075
95-th percentile0.999960.9999615
Maximum0.999990.99998
Range0.999570020.99891388
Interquartile range (IQR)0.000240.00041

Descriptive statistics

 Profiling ReportTransformed Data
Standard deviation0.365301040.3966355
Coefficient of variation (CV)0.434880860.49304331
Kurtosis1.41753520.39098316
Mean0.840002570.80446381
Median Absolute Deviation (MAD)0.000110.00013
Skewness-1.8485384-1.5447176
Sum8506.706127.10528
Variance0.133444850.15731972
MonotonicityNot monotonicNot monotonic
2023-11-09T11:55:17.837930image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.99989 631
 
6.2%
0.99994 551
 
5.4%
0.99981 478
 
4.7%
0.9999 452
 
4.5%
0.99993 394
 
3.9%
0.99988 391
 
3.9%
0.99982 373
 
3.7%
0.9998 344
 
3.4%
0.99991 341
 
3.4%
0.99969 322
 
3.2%
Other values (630) 5850
57.8%
ValueCountFrequency (%)
0.99993 10
 
6.3%
0.9998 10
 
6.3%
0.99989 8
 
5.1%
0.99969 7
 
4.4%
0.99991 7
 
4.4%
0.99994 6
 
3.8%
0.9999 6
 
3.8%
0.99981 5
 
3.2%
0.99982 5
 
3.2%
0.99983 5
 
3.2%
Other values (59) 89
56.3%
ValueCountFrequency (%)
0.00041998 2
< 0.1%
0.00042446 1
 
< 0.1%
0.00046237 1
 
< 0.1%
0.00055285 3
< 0.1%
0.00055875 2
< 0.1%
0.0005616 1
 
< 0.1%
0.00056181 1
 
< 0.1%
0.00056902 1
 
< 0.1%
0.00057979 1
 
< 0.1%
0.00058361 1
 
< 0.1%
ValueCountFrequency (%)
0.00106612 1
0.6%
0.00127462 1
0.6%
0.00155735 1
0.6%
0.00162275 1
0.6%
0.00179304 1
0.6%
0.00193323 1
0.6%
0.00258725 1
0.6%
0.00272694 1
0.6%
0.00284317 1
0.6%
0.00305523 1
0.6%
ValueCountFrequency (%)
0.00106612 1
< 0.1%
0.00127462 1
< 0.1%
0.00155735 1
< 0.1%
0.00162275 1
< 0.1%
0.00179304 1
< 0.1%
0.00193323 1
< 0.1%
0.00258725 1
< 0.1%
0.00272694 1
< 0.1%
0.00284317 1
< 0.1%
0.00305523 1
< 0.1%
ValueCountFrequency (%)
0.00041998 2
1.3%
0.00042446 1
 
0.6%
0.00046237 1
 
0.6%
0.00055285 3
1.9%
0.00055875 2
1.3%
0.0005616 1
 
0.6%
0.00056181 1
 
0.6%
0.00056902 1
 
0.6%
0.00057979 1
 
0.6%
0.00058361 1
 
0.6%

Interactions

Profiling Report

2023-11-09T11:54:31.740363image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.871952image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.422546image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.628360image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.651713image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.801787image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.781058image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.872775image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.933979image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.891289image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.037498image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.868198image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.279557image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.985657image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.448292image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.162124image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.619229image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.176776image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.925119image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.208971image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.080998image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.210007image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.292911image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.279616image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.602805image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.538416image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.815069image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.626456image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.991593image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.643799image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.195633image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.707582image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.464839image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.725380image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.817486image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.938547image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.493631image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.685375image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.704194image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.868186image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.849654image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.918977image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.997270image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.935115image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.106236image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.943363image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.346806image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.051563image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.516411image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.210250image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.687795image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.226802image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.991802image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.259801image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.152477image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.274581image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.362190image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.343301image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.671380image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.601150image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.884536image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.696202image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.061280image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.709543image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.264780image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.764759image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.537403image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.790856image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.887255image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.157751image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.559523image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.752116image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.777714image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.935366image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.916370image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.994383image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.060270image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.001778image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.249858image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.011293image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.411695image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.114001image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.581144image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.276817image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.756623image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.303470image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.055766image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.326395image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.217181image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.326581image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.429898image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.410892image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.737874image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.667413image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.949328image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.759987image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.126458image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.776608image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.327589image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.826547image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.608047image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.861508image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.960040image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.204219image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.625144image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.801971image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.841766image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.000066image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.981169image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.035452image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.122884image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.051405image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.327482image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.072644image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.462074image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.171673image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.645892image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.340016image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.825301image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.361155image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.120172image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.375753image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.285902image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.398372image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.497627image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.460011image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.805359image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.728590image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.015101image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.809882image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.196228image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.840974image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.395292image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.875695image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.680044image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.927236image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.028357image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.279430image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.687836image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.866803image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.887640image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.056050image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.040812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.102623image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.170446image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.117654image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.379028image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.118809image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.537261image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.218168image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.695307image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.393600image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.887991image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.410354image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.182013image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.426582image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.349567image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.443218image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.562835image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.526479image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.869044image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.776197image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.077538image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.862987image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.260844image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.896078image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.445091image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.925935image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.750031image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.975841image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.100026image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.353968image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.753669image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.933984image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.962519image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.122813image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.106379image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.168982image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.237653image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.168454image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.445565image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.201993image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.602824image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.285257image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.774386image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.458196image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.945352image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.476834image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.248683image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.504983image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.417341image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.522110image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.634746image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.600308image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.937805image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.857742image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.144410image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.926358image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.331888image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.962708image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.511705image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.004418image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.823847image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.060541image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.176702image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.417564image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.886022image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:53.993433image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.029154image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.184504image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.171026image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.218561image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.303900image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.235295image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.512446image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.266699image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.670507image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.334511image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.842217image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.516123image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.026324image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.526062image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.316333image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.562037image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.478977image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.581704image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.706132image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.663433image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.010536image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.922359image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.214967image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.996212image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.402220image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.024424image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.692955image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.061764image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.899518image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.126297image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.251293image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.482657image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:12.956839image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.051310image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.087902image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.235162image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.237425image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.282665image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.370749image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.285295image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.578644image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.318516image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.738239image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.408862image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.910538image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.560325image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.097718image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.596457image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.385231image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.610780image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.560606image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.645206image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.776336image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.725498image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.080791image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.983589image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.283580image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.043347image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.474809image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.084600image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.756596image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.110289image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.973719image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.190816image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.329428image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.546892image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.026145image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.102078image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.154107image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.304317image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.313567image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.335245image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.436590image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.334902image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.655934image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.385811image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.808978image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.467544image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.980004image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.627388image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.168270image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.643079image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.455700image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.674566image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.633873image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.693198image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.849936image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.776205image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.146375image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.043164image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.354760image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.109767image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.546703image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.145178image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.830499image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.176100image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.053034image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.242384image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.401051image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.612555image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.092335image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.151963image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.230145image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.352001image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.370985image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.384922image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.500226image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.402482image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.712179image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.452171image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.875407image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.517746image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.048643image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.676065image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.238940image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.709205image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.520459image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.726614image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.701144image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.762437image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.917038image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.847208image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.211936image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.092426image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.421015image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.163738image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.616885image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.192565image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.895257image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.225532image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.126319image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.317548image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.480653image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.679252image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.163545image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.331131image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.299366image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.418988image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.446276image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.454030image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.567289image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.463062image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.791075image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.518348image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.946285image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.584270image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.112430image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.745573image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.310173image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.759777image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.589992image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.776538image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.774114image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.825536image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.990124image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.912930image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.297988image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.174391image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.491759image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.226351image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.688615image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.266386image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.967661image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.294067image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.204739image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.384578image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.556977image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.750853image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.232367image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.413608image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.367485image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.490470image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.503853image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.517703image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.635282image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.523640image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.860812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.585321image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.018382image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.635278image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.193700image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.812115image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.477782image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.826395image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.661943image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.843155image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.847922image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.877236image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.063496image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.980482image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.370994image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.245267image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.564445image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.291075image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.761172image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.326539image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.039455image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.342806image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.283694image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.454947image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.634458image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.823323image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.303527image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.493021image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.435943image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.558227image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.587050image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.568696image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.702192image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.587238image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.932322image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.651943image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.088127image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.851013image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.264817image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.875835image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.556304image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.898448image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.729934image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.910231image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.922179image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.957894image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.134865image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.054128image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.443219image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.311944image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.634601image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.357175image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.833451image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.397015image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.111506image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.421710image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.360867image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.527396image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.710056image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.875823image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.370202image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.556152image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.502399image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.616822image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.652188image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.635325image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.753902image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.635507image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:17.999774image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.718587image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.158781image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.910903image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.334119image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.926452image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.630274image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.954137image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.799300image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.959350image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:23.994339image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.009769image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.207058image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.116916image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.522100image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.362425image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.703122image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.413752image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.904175image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.443351image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.179394image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.476018image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.437450image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.591899image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.786224image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:11.942622image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.441213image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.627796image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.570160image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.668666image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.724025image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.702991image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.820451image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.700149image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.069587image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.791300image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.229489image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:59.975845image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.405225image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.995501image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.702177image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.010047image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.869349image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.030645image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.070029image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.081568image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.279177image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.176357image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.596511image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.441500image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.773879image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.464139image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:28.976924image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.509827image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.253067image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.525761image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.515899image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.660621image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.858885image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:12.019589image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.506452image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.685593image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.636772image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.734987image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.788563image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.751769image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.890805image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.754015image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.136221image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.853475image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.296809image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.026366image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.473535image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.052827image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.772353image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.076743image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.928773image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.076458image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.140827image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.143148image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.349375image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.389369image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.661885image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.493366image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.842853image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.526537image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.045187image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.575362image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.319281image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.595075image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.588345image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.727232image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:32.936187image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:12.090292image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:13.578165image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:54.751256image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:14.708404image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:55.805150image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:15.863294image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:56.818599image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:16.954213image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:57.802404image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:18.206796image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:54:58.922564image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:19.369438image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:00.098508image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:20.546012image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:01.117860image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:21.848987image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:02.141336image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:22.998538image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:03.143116image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:24.219143image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:04.211905image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:25.423862image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:05.468782image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:26.728582image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:06.562830image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:27.916814image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:07.593158image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:29.120813image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:08.641549image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:30.393057image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:09.660684image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

2023-11-09T11:54:31.662123image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:10.797885image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

Profiling Report

2023-11-09T11:55:17.932228image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Transformed Data

2023-11-09T11:55:18.112130image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Profiling Report

CLIENTNUMCustomer_AgeDependent_countMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2Attrition_FlagGenderEducation_LevelMarital_StatusIncome_CategoryCard_Category
CLIENTNUM1.0000.017-0.0040.1110.014-0.0080.0110.0140.0030.0110.024-0.0020.0060.0160.007-0.0300.0300.0480.0140.0150.0060.0030.000
Customer_Age0.0171.000-0.1440.769-0.0140.044-0.0140.0020.014-0.002-0.071-0.039-0.054-0.0400.0110.001-0.0020.0240.0000.0140.0820.0840.021
Dependent_count-0.004-0.1441.000-0.115-0.036-0.009-0.0410.051-0.0040.054-0.0260.0580.0530.009-0.0350.045-0.0430.0210.0000.0010.0370.0430.018
Months_on_book0.1110.769-0.1151.000-0.0140.057-0.0080.0070.0060.008-0.054-0.029-0.039-0.034-0.0040.012-0.0130.0190.0110.0020.0430.0460.013
Total_Relationship_Count0.014-0.014-0.036-0.0141.000-0.0070.061-0.0590.012-0.0710.026-0.279-0.2270.0240.065-0.0290.0290.1660.0000.0000.0220.0070.067
Months_Inactive_12_mon-0.0080.044-0.0090.057-0.0071.0000.030-0.028-0.043-0.016-0.019-0.032-0.051-0.047-0.0270.558-0.5570.1960.0190.0000.0070.0170.000
Contacts_Count_12_mon0.011-0.014-0.041-0.0080.0610.0301.0000.023-0.0450.033-0.021-0.167-0.168-0.093-0.0590.644-0.6460.2390.0590.0000.0070.0150.010
Credit_Limit0.0140.0020.0510.007-0.059-0.0280.0231.0000.1310.9310.0210.0280.034-0.011-0.417-0.0230.0230.0320.4390.0000.0260.2780.335
Total_Revolving_Bal0.0030.014-0.0040.0060.012-0.043-0.0450.1311.000-0.1540.0360.0180.0400.0780.709-0.1530.1520.4020.0330.0070.0120.0220.019
Avg_Open_To_Buy0.011-0.0020.0540.008-0.071-0.0160.0330.931-0.1541.0000.0070.0220.022-0.040-0.6860.023-0.0230.0190.4400.0000.0280.2780.337
Total_Amt_Chng_Q4_Q10.024-0.071-0.026-0.0540.026-0.019-0.0210.0210.0360.0071.0000.1350.0850.3020.033-0.0640.0640.1840.0440.0000.0530.0150.024
Total_Trans_Amt-0.002-0.0390.058-0.029-0.279-0.032-0.1670.0280.0180.0220.1351.0000.8800.2230.019-0.2100.2110.3250.2470.0120.1040.0930.154
Total_Trans_Ct0.006-0.0540.053-0.039-0.227-0.051-0.1680.0340.0400.0220.0850.8801.0000.2330.040-0.2900.2900.4580.1630.0040.0990.0560.109
Total_Ct_Chng_Q4_Q10.016-0.0400.009-0.0340.024-0.047-0.093-0.0110.078-0.0400.3020.2230.2331.0000.094-0.2130.2140.3140.0500.0000.0300.0230.000
Avg_Utilization_Ratio0.0070.011-0.035-0.0040.065-0.027-0.059-0.4170.709-0.6860.0330.0190.0400.0941.000-0.1520.1520.2410.2790.0000.0270.1650.149
Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1-0.0300.0010.0450.012-0.0290.5580.644-0.023-0.1530.023-0.064-0.210-0.290-0.213-0.1521.000-1.0001.0000.0360.0250.0170.0280.000
Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_20.030-0.002-0.043-0.0130.029-0.557-0.6460.0230.152-0.0230.0640.2110.2900.2140.152-1.0001.0001.0000.0360.0250.0170.0280.000
Attrition_Flag0.0480.0240.0210.0190.1660.1960.2390.0320.4020.0190.1840.3250.4580.3140.2411.0001.0001.0000.0360.0250.0170.0280.000
Gender0.0140.0000.0000.0110.0000.0190.0590.4390.0330.4400.0440.2470.1630.0500.2790.0360.0360.0361.0000.0110.0090.8390.084
Education_Level0.0150.0140.0010.0020.0000.0000.0000.0000.0070.0000.0000.0120.0040.0000.0000.0250.0250.0250.0111.0000.0110.0170.000
Marital_Status0.0060.0820.0370.0430.0220.0070.0070.0260.0120.0280.0530.1040.0990.0300.0270.0170.0170.0170.0090.0111.0000.0080.028
Income_Category0.0030.0840.0430.0460.0070.0170.0150.2780.0220.2780.0150.0930.0560.0230.1650.0280.0280.0280.8390.0170.0081.0000.053
Card_Category0.0000.0210.0180.0130.0670.0000.0100.3350.0190.3370.0240.1540.1090.0000.1490.0000.0000.0000.0840.0000.0280.0531.000

Transformed Data

CLIENTNUMCustomer_AgeDependent_countMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2Attrition_FlagGenderEducation_LevelMarital_StatusIncome_Category
CLIENTNUM1.0000.111-0.1850.205-0.004-0.0410.127-0.052-0.188-0.0380.0350.0060.018-0.012-0.0400.074-0.0710.0000.1020.0000.0990.073
Customer_Age0.1111.000-0.3220.8010.021-0.0510.039-0.107-0.080-0.1020.012-0.003-0.0590.0380.073-0.0240.0220.1120.0000.0950.0550.000
Dependent_count-0.185-0.3221.000-0.252-0.0670.078-0.0070.003-0.0260.0040.0180.1630.0830.035-0.0350.161-0.1570.1650.0000.0690.0540.093
Months_on_book0.2050.801-0.2521.000-0.0040.0020.023-0.141-0.131-0.1300.0130.0860.004-0.0020.077-0.0170.0160.0000.0000.0000.1640.046
Total_Relationship_Count-0.0040.021-0.067-0.0041.000-0.0980.101-0.033-0.107-0.016-0.069-0.090-0.0240.091-0.063-0.0930.0900.2300.0000.0000.0000.000
Months_Inactive_12_mon-0.041-0.0510.0780.002-0.0981.0000.1360.001-0.0550.0050.099-0.010-0.023-0.095-0.0460.549-0.5510.3170.0630.0000.0000.000
Contacts_Count_12_mon0.1270.039-0.0070.0230.1010.1361.000-0.108-0.153-0.0930.071-0.065-0.075-0.0120.0130.693-0.6930.1970.1080.0730.0000.000
Credit_Limit-0.052-0.1070.003-0.141-0.0330.001-0.1081.0000.1010.9930.016-0.100-0.080-0.195-0.775-0.0860.0880.0000.2690.0000.0000.172
Total_Revolving_Bal-0.188-0.080-0.026-0.131-0.107-0.055-0.1530.1011.000-0.0030.0590.1070.1830.0940.489-0.2490.2490.5640.0000.1350.1240.039
Avg_Open_To_Buy-0.038-0.1020.004-0.130-0.0160.005-0.0930.993-0.0031.0000.005-0.117-0.107-0.216-0.839-0.0550.0570.0000.2390.0000.0000.111
Total_Amt_Chng_Q4_Q10.0350.0120.0180.013-0.0690.0990.0710.0160.0590.0051.0000.0720.0070.3050.0290.086-0.0820.0900.2790.0000.0000.169
Total_Trans_Amt0.006-0.0030.1630.086-0.090-0.010-0.065-0.1000.107-0.1170.0721.0000.8810.2610.158-0.2110.2140.4020.0980.0780.0000.000
Total_Trans_Ct0.018-0.0590.0830.004-0.024-0.023-0.075-0.0800.183-0.1070.0070.8811.0000.2560.200-0.2940.2960.5730.0000.0000.1260.000
Total_Ct_Chng_Q4_Q1-0.0120.0380.035-0.0020.091-0.095-0.012-0.1950.094-0.2160.3050.2610.2561.0000.248-0.2000.1980.2760.1790.0570.0210.000
Avg_Utilization_Ratio-0.0400.073-0.0350.077-0.063-0.0460.013-0.7750.489-0.8390.0290.1580.2000.2481.000-0.1150.1150.4160.2230.0720.2630.177
Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_10.074-0.0240.161-0.017-0.0930.5490.693-0.086-0.249-0.0550.086-0.211-0.294-0.200-0.1151.000-0.9990.9800.0000.0000.0000.163
Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2-0.0710.022-0.1570.0160.090-0.551-0.6930.0880.2490.057-0.0820.2140.2960.1980.115-0.9991.0000.9800.0000.0000.0000.163
Attrition_Flag0.0000.1120.1650.0000.2300.3170.1970.0000.5640.0000.0900.4020.5730.2760.4160.9800.9801.0000.0000.0000.0000.163
Gender0.1020.0000.0000.0000.0000.0630.1080.2690.0000.2390.2790.0980.0000.1790.2230.0000.0000.0001.0000.0000.1490.792
Education_Level0.0000.0950.0690.0000.0000.0000.0730.0000.1350.0000.0000.0780.0000.0570.0720.0000.0000.0000.0001.0000.0270.000
Marital_Status0.0990.0550.0540.1640.0000.0000.0000.0000.1240.0000.0000.0000.1260.0210.2630.0000.0000.0000.1490.0271.0000.000
Income_Category0.0730.0000.0930.0460.0000.0000.0000.1720.0390.1110.1690.0000.0000.0000.1770.1630.1630.1630.7920.0000.0001.000

Missing values

Profiling Report

2023-11-09T11:54:33.049298image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.

Transformed Data

2023-11-09T11:55:12.192420image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.

Profiling Report

2023-11-09T11:54:33.267172image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Transformed Data

2023-11-09T11:55:12.398214image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Profiling Report

CLIENTNUMAttrition_FlagCustomer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2
0768805383Existing Customer45M3High SchoolMarried$60K - $80KBlue3951312691.077711914.01.3351144421.6250.0610.0000930.99991
1818770008Existing Customer49F5GraduateSingleLess than $40KBlue446128256.08647392.01.5411291333.7140.1050.0000570.99994
2713982108Existing Customer51M3GraduateMarried$80K - $120KBlue364103418.003418.02.5941887202.3330.0000.0000210.99998
3769911858Existing Customer40F4High SchoolUnknownLess than $40KBlue343413313.02517796.01.4051171202.3330.7600.0001340.99987
4709106358Existing Customer40M3UneducatedMarried$60K - $80KBlue215104716.004716.02.175816282.5000.0000.0000220.99998
5713061558Existing Customer44M2GraduateMarried$40K - $60KBlue363124010.012472763.01.3761088240.8460.3110.0000550.99994
6810347208Existing Customer51M4UnknownMarried$120K +Gold4661334516.0226432252.01.9751330310.7220.0660.0001230.99988
7818906208Existing Customer32M0High SchoolUnknown$60K - $80KSilver2722229081.0139627685.02.2041538360.7140.0480.0000860.99991
8710930508Existing Customer37M3UneducatedSingle$60K - $80KBlue3652022352.0251719835.03.3551350241.1820.1130.0000450.99996
9719661558Existing Customer48M2GraduateSingle$80K - $120KBlue3663311656.016779979.01.5241441320.8820.1440.0003030.99970

Transformed Data

CLIENTNUMAttrition_FlagCustomer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2
38715190283Existing Customer57F1GraduateUnknown$40K - $60KBlue493323672.08862786.01.3201464280.5560.2410.0001690.999830
58711427458Existing Customer44F5GraduateMarriedUnknownBlue354126273.09785295.02.2751359251.0830.1560.0000570.999940
258714187533Existing Customer45F2UneducatedSingle$40K - $60KBlue352303540.08492691.00.4561321280.7500.2400.0000680.999930
509716223708Attrited Customer45F3UneducatedSingleUnknownBlue363334028.07103318.00.731791220.8330.1760.9969100.003088
573715416633Existing Customer54M1UnknownMarried$80K - $120KBlue364126175.09605215.00.7091847590.4050.1550.0000570.999940
622711628458Existing Customer45F3GraduateMarriedLess than $40KBlue314108829.09017928.00.8251902450.6670.1020.0000210.999980
716789291633Existing Customer62M0GraduateMarried$60K - $80KBlue513205450.09674483.00.7011526450.8000.1770.0000360.999960
771715271733Existing Customer50F2UneducatedSingleLess than $40KBlue373308520.08147706.00.5041193350.3460.0960.0000680.999930
950788814783Existing Customer39M1UneducatedSingle$60K - $80KBlue224339204.08458359.00.6731820580.6110.0920.0002920.999710
1005772532208Attrited Customer51F2DoctorateMarriedLess than $40KBlue412236630.09165714.00.927842240.5000.1380.9964000.003596

Profiling Report

CLIENTNUMAttrition_FlagCustomer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2
10117712503408Existing Customer57M2GraduateMarried$80K - $120KBlue4063417925.0190916016.00.712174981110.8200.1060.0005160.999480
10118713755458Attrited Customer50M1UnknownUnknown$80K - $120KBlue366349959.09529007.00.82510310631.1000.0960.9981300.001874
10119716893683Attrited Customer55F3UneducatedSingleUnknownBlue4743314657.0251712140.00.1666009530.5140.1720.9969100.003088
10120710841183Existing Customer54M1High SchoolSingle$60K - $80KBlue3452013940.0210911831.00.660155771140.7540.1510.0000380.999960
10121713899383Existing Customer56F1GraduateSingleLess than $40KBlue504143688.06063082.00.570145961200.7910.1640.0001480.999850
10122772366833Existing Customer50M2GraduateSingle$40K - $60KBlue403234003.018512152.00.703154761170.8570.4620.0001910.999810
10123710638233Attrited Customer41M2UnknownDivorced$40K - $60KBlue254234277.021862091.00.8048764690.6830.5110.9952700.004729
10124716506083Attrited Customer44F1High SchoolMarriedLess than $40KBlue365345409.005409.00.81910291600.8180.0000.9978800.002118
10125717406983Attrited Customer30M2GraduateUnknown$40K - $60KBlue364335281.005281.00.5358395620.7220.0000.9967100.003294
10126714337233Attrited Customer43F2GraduateMarriedLess than $40KSilver2562410388.019618427.00.70310294610.6490.1890.9966200.003377

Transformed Data

CLIENTNUMAttrition_FlagCustomer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2
9834788019483Existing Customer49M3GraduateMarried$80K - $120KBlue404133660.07662894.00.535145151220.8480.2090.0000960.99990
9864720633558Existing Customer37F3GraduateDivorcedLess than $40KBlue243343727.09952732.00.743147861010.6560.2670.0005350.99946
9895708880683Existing Customer49M5CollegeMarried$40K - $60KBlue404343970.08923078.00.772136971020.7590.2250.0005180.99948
9929779082633Existing Customer30M2UneducatedSingle$60K - $80KBlue133234107.09793128.00.647145961040.7330.2380.0001970.99980
9993719934783Existing Customer43M3DoctorateMarried$80K - $120KBlue274223676.06733003.00.629146511050.7800.1830.0001710.99983
10037789398733Existing Customer56M3GraduateMarried$120K +Blue463325270.07794491.00.731161791050.6940.1480.0001870.99981
10041767348733Existing Customer56M2UnknownMarried$60K - $80KBlue493334058.07933265.00.758158651050.6670.1950.0003330.99967
10087713768358Existing Customer45M4GraduateSingle$40K - $60KBlue353227935.08887047.00.779153801220.6940.1120.0001190.99988
10099709094358Existing Customer51F1GraduateSingleLess than $40KBlue414238900.07988102.00.64716737880.6600.0900.0001800.99982
10121713899383Existing Customer56F1GraduateSingleLess than $40KBlue504143688.06063082.00.570145961200.7910.1640.0001480.99985

Duplicate rows

Profiling Report

CLIENTNUMAttrition_FlagCustomer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2# duplicates
Dataset does not contain duplicate rows.

Transformed Data

CLIENTNUMAttrition_FlagCustomer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioNaive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_1Naive_Bayes_Classifier_Attrition_Flag_Card_Category_Contacts_Count_12_mon_Dependent_count_Education_Level_Months_Inactive_12_mon_2# duplicates
Dataset does not contain duplicate rows.